The concept of crowdsourcing has been popular lately, but not everything is easily sourced out to the crowd. Netflix is trying their hand at the game by throwing a little money into the pot. They're offering a million dollars to anyone who can improve the accuracy of their movie recommendation engine. Of course, there are some questions here. They claim they'll award the prize to whoever makes their system 10% or more accurate -- but it's not clear (at least from the NY Times article) how "accuracy" is determined. While some people do seem excited that Netflix has released a very large dataset for people to work on, part of this seems like an attempt to get a lot of free labor by making it a contest. It's true that contests like the X-Prize for space flight and the Grand Challenge for autonomous vehicles helped spur a lot of innovation -- but both were in general areas where the research efforts could easily lead to entire new industries. With a better recommendation system, it's basically just to help Netflix. And, to be honest, it just doesn't seem as exciting to help Netflix help you pick a better movie using collaborative filtering as it does to shoot a rocket into space. Still, this is an interesting trend, and you have to wonder if other companies will start experimenting with this "winner takes all" form of outsourcing -- or if people realize that all of the losers end up with nothing. Companies have plenty to gain if such programs work out -- but it seems like plenty of people will question whether it's worth building new tools for a company when they might not even get paid for it.
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